Coalition for Secure AI Unveils Five-Layer Framework to Clarify AI Accountability and Compliance
Key Takeaways
- ▸CosAI introduced a five-layer accountability model that clarifies responsibility across the AI stack, filling a gap left by traditional cloud shared responsibility frameworks
- ▸The framework's new 'AI Model Provider' layer explicitly assigns foundation model suppliers responsibility for vulnerability disclosure, training data transparency, and known security weaknesses
- ▸The framework addresses modern AI governance challenges including autonomous agents, shadow AI, and complex multi-jurisdictional regulations that traditional frameworks don't cover
Summary
The Coalition for Secure AI (CosAI) has released the AI Shared Responsibility Framework, a five-layer governance model designed to clarify accountability across the entire AI technology stack. Released following sessions at RSAC 2026, the framework addresses a critical problem: when AI systems fail or violate compliance requirements, responsibility is unclear because traditional cloud governance models were never designed for the complexity of modern AI—which involves foundation models, multiple vendors, autonomous agents, and cascading regulatory requirements.
The framework divides AI accountability into five explicit layers: AI Business and Usage (governance and regulatory compliance), AI Information (data ownership and shadow AI management), AI Application (developer responsibilities for integration and safety), AI Platform (infrastructure provider obligations including compute security and identity management), and AI Model Provider (a new layer addressing foundation model accountability). Each layer assigns exactly one responsible party, eliminating ambiguity about who owns specific aspects of AI system security, safety, and compliance—designed to accelerate incident response and problem resolution.
The framework is particularly significant because it addresses gaps unacknowledged by traditional governance models: agentic systems taking autonomous actions, employees using unsanctioned external AI tools (shadow AI), and AI-specific regulations (FDA guidance for medical AI, EU AI Act requirements, financial services model risk management) that cut across traditional compliance frameworks. By explicitly assigning model providers responsibility for prompt injection vulnerability documentation, training data provenance, and vulnerability disclosure processes, the framework closes a critical gap in the AI supply chain.
- Each of the five layers (Business/Usage, Information, Application, Platform, Model Provider) assigns exactly one responsible party, designed to enable faster incident response and compliance
Editorial Opinion
The AI Shared Responsibility Framework addresses a genuine and urgent need as AI systems become embedded in critical business operations and regulated industries. By providing a clear, five-layer blueprint for accountability, CosAI signals that the AI industry is maturing toward operational governance practices comparable to traditional cloud infrastructure. This framework could become the standard reference for organizations navigating AI governance, particularly in regulated sectors like healthcare and finance where compliance gaps create material risk.
